Increased similarity of neural responses to experienced and empathic distress in costly altruism Article

O’Connell, K, Brethel-Haurwitz, KM, Rhoads, SA et al. (2019). Increased similarity of neural responses to experienced and empathic distress in costly altruism . 9(1), 10.1038/s41598-019-47196-3

cited authors

  • O’Connell, K; Brethel-Haurwitz, KM; Rhoads, SA; Cardinale, EM; Vekaria, KM; Robertson, EL; Walitt, B; VanMeter, JW; Marsh, AA

abstract

  • Empathy—affective resonance with others’ sensory or emotional experiences—is hypothesized to be an important precursor to altruism. However, it is not known whether real-world altruists’ heightened empathy reflects true self-other mapping of multi-voxel neural response patterns. We investigated this relationship in adults who had engaged in extraordinarily costly real-world altruism: donating a kidney to a stranger. Altruists and controls completed fMRI testing while anticipating and experiencing pain, and watching as a stranger anticipated and experienced pain. Machine learning classifiers tested for shared representation between experienced and observed distress. Altruists exhibited more similar representations of experienced and observed fearful anticipation spontaneously and following an empathy prompt in anterior insula and anterior/middle cingulate cortex, respectively, suggesting heightened empathic proclivities and abilities for fear. During pain epochs, altruists were distinguished by spontaneous empathic responses in anterior insula, anterior/mid-cingulate cortex and supplementary motor area, but showed no difference from controls after the empathy prompt. These findings (1) link shared multi-voxel representations of the distress of self and others to real-world costly altruism, (2) reinforce distinctions between empathy for sensory states like pain and anticipatory affective states like fear, and (3) highlight the importance of differentiating between the proclivity and ability to empathize.

publication date

  • December 1, 2019

Digital Object Identifier (DOI)

volume

  • 9

issue

  • 1